OpenRaiser/Intern-Atlas huggingface dataset:
Availability Aware Continuous Replica Placement Problem
Venue: arXiv cs.DC 2016
Year: 2016

Replica placement (RP) intended at producing a set of duplicated data items across the nodes of a distributed system in order to optimize fault tolerance, availability, system performance load balancing. Typically, RP formulations employ dynamic methods to change the replica placement in the system potentially upon user request profile. Continuous Replica Placement Problem (CRPP) is an extension of replica placement problem that takes into consideration the current replication state of the distributed system along with user request profile to define a new replication scheme, subject to optimization criteria and constraints. This paper proposes an alternative technique, named Availability Aware Continuous Replica Placement Problem (AACRPP).AACRPP can be defined as: Given an already defined replica placement scheme, a user request profile, and a node failure profile define a new replication scheme, subject to optimization criteria and constraints. In this effort we use modified greedy heuristics from the CRPP and investigated the proposed mechanism using a trace driven java based simulation.
Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets, and Complexity
Venue: arXiv cs.AI 2016
Year: 2016

The challenging task of learning structures of probabilistic graphical models is an important problem within modern AI research. Recent years have witnessed several major algorithmic advances in structure learning for Bayesian networks---arguably the most central class of graphical models---especially in what is known as the score-based setting. A successful generic approach to optimal Bayesian network structure learning (BNSL), based on integer programming (IP), is implemented in the GOBNILP system. Despite the recent algorithmic advances, current understanding of foundational aspects underlying the IP based approach to BNSL is still somewhat lacking. Understanding fundamental aspects of cutting planes and the related separation problem( is important not only from a purely theoretical perspective, but also since it holds out the promise of further improving the efficiency of state-of-the-art approaches to solving BNSL exactly. In this paper, we make several theoretical contributions towards these goals: (i) we study the computational complexity of the separation problem, proving that the problem is NP-hard; (ii) we formalise and analyse the relationship between three key polytopes underlying the IP-based approach to BNSL; (iii) we study the facets of the three polytopes both from the theoretical and practical perspective, providing, via exhaustive computation, a complete enumeration of facets for low-dimensional family-variable polytopes; and, furthermore, (iv) we establish a tight connection of the BNSL problem to the acyclic subgraph problem.
Diversity of Low-Density Lattices
Venue: arXiv cs.IT 2016
Year: 2016

The non-ergodic fading channel is a useful model for various wireless communication channels in both indoor and outdoor environments. Building on Poltyrev's work on infinite lattice constellations for the Gaussian channel, we derive a Poltyrev outage limit (POL) for lattices in presence of block fading. We prove that the diversity order of this POL is equal to the number of degrees of freedom in the channel. Further, we describe full-diversity constructions of real lattices defined by their integer-check matrix, i.e., the inverse of their generator matrix. In the first construction suited to maximum-likelihood decoding, these lattices are defined by sparse (low-density) or non-sparse integer-check matrices. Based on a special structure of the lattice binary image, a second full-diversity lattice construction is described for sparse integer-check matrices in the context of iterative probabilistic decoding. Full diversity is theoretically proved in both cases. We also propose a method to construct lattices for diversity order 4 suitable for iterative probabilistic decoding. Computer simulation results for diversity order L = 2 and L = 4 confirm that the proposed low-density lattices attain the maximal diversity order. The newly defined POL is used during this simulation to declare an outage error without decoding, which drastically improves the decoding runtime.
Scalable Information Inequalities for Uncertainty Quantification
Venue: arXiv cs.IT 2016
Year: 2016

In this paper we demonstrate the only available scalable information bounds for quantities of interest of high dimensional probabilistic models. Scalability of inequalities allows us to (a) obtain uncertainty quantification bounds for quantities of interest in the large degree of freedom limit and/or at long time regimes; (b) assess the impact of large model perturbations as in nonlinear response regimes in statistical mechanics; (c) address model-form uncertainty, i.e. compare different extended models and corresponding quantities of interest. We demonstrate some of these properties by deriving robust uncertainty quantification bounds for phase diagrams in statistical mechanics models.
Functional lower bounds for arithmetic circuits and connections to boolean circuit complexity
Venue: arXiv cs.CC 2016
Year: 2016

We say that a circuit $C$ over a field $F$ functionally computes an $n$-variate polynomial $P$ if for every $x \in \{0,1\}^n$ we have that $C(x) = P(x)$. This is in contrast to syntactically computing $P$, when $C \equiv P$ as formal polynomials. In this paper, we study the question of proving lower bounds for homogeneous depth-$3$ and depth-$4$ arithmetic circuits for functional computation. We prove the following results : 1. Exponential lower bounds homogeneous depth-$3$ arithmetic circuits for a polynomial in $VNP$. 2. Exponential lower bounds for homogeneous depth-$4$ arithmetic circuits with bounded individual degree for a polynomial in $VNP$. Our main motivation for this line of research comes from our observation that strong enough functional lower bounds for even very special depth-$4$ arithmetic circuits for the Permanent imply a separation between ${\#}P$ and $ACC$. Thus, improving the second result to get rid of the bounded individual degree condition could lead to substantial progress in boolean circuit complexity. Besides, it is known from a recent result of Kumar and Saptharishi [KS15] that over constant sized finite fields, strong enough average case functional lower bounds for homogeneous depth-$4$ circuits imply superpolynomial lower bounds for homogeneous depth-$5$ circuits. Our proofs are based on a family of new complexity measures called shifted evaluation dimension, and might be of independent interest.
OBDA Constraints for Effective Query Answering (Extended Version)
Venue: arXiv cs.DB 2016
Year: 2016

In Ontology Based Data Access (OBDA) users pose SPARQL queries over an ontology that lies on top of relational datasources. These queries are translated on-the-fly into SQL queries by OBDA systems. Standard SPARQL-to-SQL translation techniques in OBDA often produce SQL queries containing redundant joins and unions, even after a number of semantic and structural optimizations. These redundancies are detrimental to the performance of query answering, especially in complex industrial OBDA scenarios with large enterprise databases. To address this issue, we introduce two novel notions of OBDA constraints and show how to exploit them for efficient query answering. We conduct an extensive set of experiments on large datasets using real world data and queries, showing that these techniques strongly improve the performance of query answering up to orders of magnitude.
Cell Associations that Maximize the Average Uplink-Downlink Degrees of Freedom
Venue: arXiv cs.IT 2016
Year: 2016

We study the problem of associating mobile terminals to base stations in a linear interference network, with the goal of maximizing the average rate achieved over both the uplink and downlink sessions. The cell association decision is made at a centralized cloud level, with access to global network topology information. More specifically, given the constraint that each mobile terminal can be associated to a maximum of N base stations at once, we characterize the maximum achievable pre-log factor (degrees of freedom) and the corresponding cell association pattern. Interestingly, the result indicates that for the case where N > 1, the optimal cell association guarantees the achievability of the maximum uplink rate even when optimizing for the uplink alone, and for the case where N=1, the optimal cell association is that of the downlink. Hence, this work draws attention to the question of characterizing network topologies for which the problem can be simplified by optimizing only for the uplink or only for the downlink.
A method of non-linear state feedback controller design based on state prediction
Venue: arXiv cs.SY 2016
Year: 2016

In this paper, we considered a design method of non-linear state feedback controller for input-affine non-linear system taking data losses into account. When data is lost in control system, control input is fixed to constant value or to the last implemented value [1,2]. When data losses are taken into account, these methods do not guarantee the stability of desired closed-loop. The proposed method guarantees the stability and robustness properties in the presence of uncertainty and data losses.
Efficient sequential compression of multi-channel biomedical signals
Venue: arXiv cs.IT 2016
Year: 2016

This work proposes lossless and near-lossless compression algorithms for multi-channel biomedical signals. The algorithms are sequential and efficient, which makes them suitable for low-latency and low-power signal transmission applications. We make use of information theory and signal processing tools (such as universal coding, universal prediction, and fast online implementations of multivariate recursive least squares), combined with simple methods to exploit spatial as well as temporal redundancies typically present in biomedical signals. The algorithms are tested with publicly available electroencephalogram and electrocardiogram databases, surpassing in all cases the current state of the art in near-lossless and lossless compression ratios.
Study of Relay Selection for Physical-Layer Security in Buffer-Aided Relay Networks Based on the Secrecy Rate Criterion
Venue: arXiv cs.IT 2016
Year: 2016

In this paper, we investigate an opportunistic relay and jammer scheme along with relay selection algorithms based on the secrecy rate criterion in multiple-input multiple-output buffer-aided down link relay networks, which consist of one source, a number of relay nodes, legitimate users and eavesdroppers, with the constraints of physical layer security. The opportunistic relay and jammer scheme is employed to improve the transmission rate and different relay selection policies are performed to achieve better secrecy rate with the consideration of eavesdroppers. Among all the investigated relay selection policies, a relay selection policy which is developed to maximize the secrecy rate based on exhaustive searches outperforms other relay selection policies in terms of secrecy rate. Based on the secrecy rate criterion, we develop a relay selection algorithm without knowledge of the channels of the eavesdroppers. We also devise a greedy search algorithm based on the secrecy rate criterion to reduce the computational complexity of the exhaustive search technique. Simulations show the superiority of the secrecy rate criterion over competing approaches.
Communicating One Bit over a Delay Constrained Gaussian MIMO Channel with Feedback
Venue: arXiv cs.IT 2016
Year: 2016

The energy-optimal scheme is found for communicating one bit over a memoryless Gaussian channel with an ideal feedback channel. It is assumed that the channel is allowed to be used at most N times before decoding. The optimal coding/decoding strategy is derived by dynamic programming. It is found that feedback gives a significant performance gain and that the optimal strategies are discontinuous. It is also shown that most of the performance increase can be obtained even with a one-bit feedback channel. The optimal scheme is compared with the strategy by Kailath-Schalkwijk and is found to be significantly more effective. For the case of a diagonal MIMO channel where measurement noise variances are equal along the sub channels we also show that the problem can be reduced to the previous case of transmitting one bit over a scalar feedback channel.
Alternating optimization method based on nonnegative matrix factorizations for deep neural networks
Venue: arXiv cs.LG 2016
Year: 2016

The backpropagation algorithm for calculating gradients has been widely used in computation of weights for deep neural networks (DNNs). This method requires derivatives of objective functions and has some difficulties finding appropriate parameters such as learning rate. In this paper, we propose a novel approach for computing weight matrices of fully-connected DNNs by using two types of semi-nonnegative matrix factorizations (semi-NMFs). In this method, optimization processes are performed by calculating weight matrices alternately, and backpropagation (BP) is not used. We also present a method to calculate stacked autoencoder using a NMF. The output results of the autoencoder are used as pre-training data for DNNs. The experimental results show that our method using three types of NMFs attains similar error rates to the conventional DNNs with BP.
Overcoming the language barrier in mobile user interface design: A case study on a mobile health app
Venue: arXiv cs.CY 2016
Year: 2016

This research report proposes a structured solution to address the need for awareness of cultural and language in user design. It will include evaluated research on established methods that already exist. Discussed ideas about how to address this situation include: what others have found to take into consideration when using design principles to develop an interface, detailed troubles and critical issues that have been previously identified and also ways that have been found already to overcome such issues. This will also involve designing a prototype application catering to resolving these issues. Overcoming the language barrier plays an important role in the process of implementing a user design interface that will satisfy users. This issue must be researched and examined to identify the issues and concerns associated in order to provide a solution in an ethical manner.
Participating or Not Participating? A Sociomaterial Perspective of the Embeddedness of Online Communities in Everyday Life
Venue: arXiv cs.CY 2016
Year: 2016

Online communities are increasingly becoming a venue for socializing, engaging in politics, and conducting business. Ironically, the same enabling social media technology is encroaching into everyday life and reconfiguring relations of participation. Yet, while participation in online communities has been widely studied empirically, theoretical aspects of this social phenomenon need further investigation. This paper uses a sociomaterial perspective to further develop theoretical explanation of participation in online communities and the impacts of not participating online. A sociomaterial view of online community participation decenters the human participant and recognises the agency of technology, thus creating a richer understanding than epistemological paradigms. Using converging hermeneutic circles, the paper first reviews literature for evidence of sociomaterial applications to online community research, and then proposes a framework for expressing participation in online communities from a sociomaterial perspective. Subsequently, implications of the findings and the potential for future studies are discussed.
Online Social Networking Has a Greater Effect on Others than on Me: A Third-Person Effect Perspective
Venue: arXiv cs.CY 2016
Year: 2016

To date, much research has been conducted on the positive and negative effects of online social networking (OSN). However, how users perceive others and themselves being subject to these effects and the consequences of users' perceptions are understudied. Drawing from the third-person effect theory, this study examines the self-other perceptual gap for positive and negative effects of OSN and the consequences of perceptions for negative effects. Findings from our online survey (N=187) and interviews (N=8) suggested a significant difference between the perceived positive and negative effects on self and on others. Furthermore, the link between the third-person perception for usage risks of OSN and support for taking privacy protection actions was confirmed. We also found that the self-other discrepant perceptions were not influenced by age, time spent on OSN, number of OSN friends. However, gender emerged as a key difference in the third-person effects gap for privacy risks.
Gearbox Fault Detection through PSO Exact Wavelet Analysis and SVM Classifier
Venue: arXiv cs.LG 2016
Year: 2016

Time-frequency methods for vibration-based gearbox faults detection have been considered the most efficient method. Among these methods, continuous wavelet transform (CWT) as one of the best time-frequency method has been used for both stationary and transitory signals. Some deficiencies of CWT are problem of overlapping and distortion ofsignals. In this condition, a large amount of redundant information exists so that it may cause false alarm or misinterpretation of the operator. In this paper a modified method called Exact Wavelet Analysis is used to minimize the effects of overlapping and distortion in case of gearbox faults. To implement exact wavelet analysis, Particle Swarm Optimization (PSO) algorithm has been used for this purpose. This method have been implemented for the acceleration signals from 2D acceleration sensor acquired by Advantech PCI-1710 card from a gearbox test setup in Amirkabir University of Technology. Gearbox has been considered in both healthy and chipped tooth gears conditions. Kernelized Support Vector Machine (SVM) with radial basis functions has used the extracted features from exact wavelet analysis for classification. The efficiency of this classifier is then evaluated with the other signals acquired from the setup test. The results show that in comparison of CWT, PSO Exact Wavelet Transform has better ability in feature extraction in price of more computational effort. In addition, PSO exact wavelet has better speed comparing to Genetic Algorithm (GA) exact wavelet in condition of equal population because of factoring mutation and crossover in PSO algorithm. SVM classifier with the extracted features in gearbox shows very good results and its ability has been proved.
Comments on "A Square-Root-Free Matrix Decomposition Method for Energy-Efficient Least Square Computation on Embedded Systems"
Venue: arXiv cs.NA 2016
Year: 2016

A square-root-free matrix QR decomposition (QRD) scheme was rederived in [1] based on [2] to simplify computations when solving least-squares (LS) problems on embedded systems. The scheme of [1] aims at eliminating both the square-root and division operations in the QRD normalization and backward substitution steps in the LS computations. It is claimed in [1] that the LS solution only requires finding the directions of the orthogonal basis of the matrix in question, regardless of the normalization of their Euclidean norms. MIMO detection problems have been named as potential applications that benefit from this. While this is true for unconstrained LS problems, we conversely show here that constrained LS problems such as MIMO detection still require computing the norms of the orthogonal basis to produce the correct result.
Pilot Pattern Adaptation for 5G MU-MIMO Wireless Communications
Venue: arXiv cs.IT 2016
Year: 2016

To meet the goal of ten-fold increase in spectral efficiency, multiuser multiple-input-multiple-output (MU-MIMO) techniques capable of achieving high spatial multiplexing gains are expected to be an essential component of fifth-generation (5G) radio access systems. This increase in multiplexing gain, made possible by equipping base stations with a large number of antennas, entails a proportional increase in channel state information (CSI) acquisition overhead. This article addresses the problem of reducing this CSI overhead by optimizing the amount of time-frequency resources allocated for channel training purposes while not affecting the quality of the associated channel estimate. First we show that in MU-MIMO, adapting pilot symbol density in the time-frequency grid should be performed both on a per resource block (RB) basis and on the basis of groups of users sharing similar channel conditions. Next, we propose a practical scheme that can perform grouping based per-RB pilot pattern adaptation. Finally, we evaluate using both analytical and numerical results the gain in spectral efficiency that can be achieved using this scheme as compared to conventional MU-MIMO systems that use fixed pilot patterns.
Monocular Urban Localization using Street View
Venue: arXiv cs.RO 2016
Year: 2016

This paper presents a metric global localization in the urban environment only with a monocular camera and the Google Street View database. We fully leverage the abundant sources from the Street View and benefits from its topo-metric structure to build a coarse-to-fine positioning, namely a topological place recognition process and then a metric pose estimation by local bundle adjustment. Our method is tested on a 3 km urban environment and demonstrates both sub-meter accuracy and robustness to viewpoint changes, illumination and occlusion. To our knowledge, this is the first work that studies the global urban localization simply with a single camera and Street View.
Structured Prediction of 3D Human Pose with Deep Neural Networks
Venue: arXiv cs.CV 2016
Year: 2016

Most recent approaches to monocular 3D pose estimation rely on Deep Learning. They either train a Convolutional Neural Network to directly regress from image to 3D pose, which ignores the dependencies between human joints, or model these dependencies via a max-margin structured learning framework, which involves a high computational cost at inference time. In this paper, we introduce a Deep Learning regression architecture for structured prediction of 3D human pose from monocular images that relies on an overcomplete auto-encoder to learn a high-dimensional latent pose representation and account for joint dependencies. We demonstrate that our approach outperforms state-of-the-art ones both in terms of structure preservation and prediction accuracy.
Revisiting XOR-based Network Coding for Energy Efficient Broadcasting in Mobile Ad Hoc Networks
Venue: arXiv cs.NI 2016
Year: 2016

Network coding is commonly used to improve the energy efficiency of network-wide broadcasting in wireless multi-hop networks. In this work, we focus on XOR-based broadcasting in mobile ad hoc networks with multiple sources. We make the observation that the common approach, which is to benefit from the synergy of XOR network coding with a CDS-based broadcast algorithm, suffers performance breakdowns. After delving into the details of this synergy, we attribute this behavior to an important mechanism of the underlying broadcast algorithm, known as the "termination criterion". To tackle the problem, we propose a termination criterion that is fully compatible with XOR coding. In addition to that, we revisit the internals of XOR coding. We first enhance the synergy of XOR coding with the underlying broadcast algorithm by allowing each mechanism to benefit from information available by the other. In this way, we manage to improve the pruning efficiency of the CDS-based algorithm while at the same time we come up with a method for detecting coding opportunities that has minimal storage and processing requirements compared to current approaches. Then, for the first time, we use XOR coding as a mechanism not only for enhancing energy efficiency but also for reducing the end-to-end-delay. We validate the effectiveness of our proposed algorithm through extensive simulations on a diverse set of scenarios.